Production Machine Learning Systems, Google Cloud

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4.5

70 ratings

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11 reviews

About this Course

In the second course of this specialization, we will dive into the components and best practices of a high-performing ML system in production environments.
Prerequisites: Basic SQL, familiarity with Python and TensorFlow...

Top reviews

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By AK

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Dec 07, 2018

It is very good course, gives good overview over large ML systems on cloud, a lot of examples from real implementations gives good understunding about problematics in projects realisations

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11 Reviews

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By Raja Ranjith Garikapati

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Dec 08, 2018

Very informative on production systems....

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By Artur Kuprijanov

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Dec 07, 2018

It is very good course, gives good overview over large ML systems on cloud, a lot of examples from real implementations gives good understunding about problematics in projects realisations

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By Hemant Devidas Kshirsagar

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Nov 25, 2018

Very Informative.

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By Michael Feldman

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Nov 11, 2018

wow gcp michael feldman

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By Carlos Viejo

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Nov 11, 2018

This Course has excellent explanations and advice on how to move your models into production and make sure they are reliables and don't lose accuracy over time. The course illustrates how to use the entire ecosystem on GCP that is impressive, quite happy with the explanation and the expert's advice.

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By Harold Lawrence Marzan Mercado

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Nov 08, 2018

Overall rating is 3 out of 5, as I expected more of the initial line in the first course. The optional Kubeflow lab has issues, as the ksonnet apply command line halts. Also, the last lab was expected to allow the student to code more, as this is the only way to make a person to gain more insights on the architecture.

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By Jun Wang

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Nov 04, 2018

This course reveals some practical techniques in Production Machine Learning Systems. I like the real world examples introduced in this course.

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By Cristobal Silva

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Oct 29, 2018

While most of the content is sufficiently informative for a course, the implementation itself has too many issues: wrong videos in some modules, errors in quizzes, and so on. Once they organize the material properly, this course can definitely be 5 stars.

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By Sinan Gabel

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Oct 27, 2018

A lot of great production examples, labs and reviews but perhaps too many issues for a single course - however I understand that it was perhaps to provide an overview of the possibilities, a kind of "toolbox" for production ML.